Efficient exploration of energy landscapes Export

@article{citeulike:5976013, abstract = {Many physical and chemical processes, such as folding of biopolymers, are best described as dynamics on large combinatorial energy landscapes. A concise approximate description of dynamics is obtained by partitioning the micro-states of the landscape into macro-states. Since most landscapes of interest are not tractable analytically, the probabilities of transitions between macro-states need to be extracted numerically from the microscopic ones, typically by full enumeration of the state space. Here we propose to approximate transition probabilities by a Markov chain Monte-Carlo method. For landscapes of the number partitioning problem and an RNA switch molecule we show that the method allows for accurate probability estimates with significantly reduced computational cost.}, archivePrefix = {arXiv}, author = {Mann, Martin and Klemm, Konstantin}, citeulike-article-id = {5976013}, citeulike-linkout-0 = {http://arxiv.org/abs/0910.2559}, citeulike-linkout-1 = {http://arxiv.org/pdf/0910.2559}, day = {14}, eprint = {0910.2559}, keywords = {free-energy, markov, mc, mutual-information, transition\_states}, month = {Oct}, posted-at = {2009-10-20 19:21:50}, priority = {2}, title = {Efficient exploration of energy landscapes}, url = {http://arxiv.org/abs/0910.2559}, year = {2009} }

TY - JOUR ID - citeulike:5976013 L3 - citeulike-article-id:5976013 N2 - Many physical and chemical processes, such as folding of biopolymers, are best described as dynamics on large combinatorial energy landscapes. A concise approximate description of dynamics is obtained by partitioning the micro-states of the landscape into macro-states. Since most landscapes of interest are not tractable analytically, the probabilities of transitions between macro-states need to be extracted numerically from the microscopic ones, typically by full enumeration of the state space. Here we propose to approximate transition probabilities by a Markov chain Monte-Carlo method. For landscapes of the number partitioning problem and an RNA switch molecule we show that the method allows for accurate probability estimates with significantly reduced computational cost. TI - Efficient exploration of energy landscapes KW - free-energy KW - markov KW - mc KW - mutual-information KW - transition_states AU - Mann, Martin AU - Klemm, Konstantin PY - 2009/Oct/14/ UR - http://arxiv.org/abs/0910.2559 ER -